eBook
Bayesian Models : A Statistical Primer for Ecologists, 2nd Edition
| Title: | Bayesian Models : A Statistical Primer for Ecologists, 2nd Edition |
|---|---|
| Description: | A fully updated and expanded edition of the essential primer on Bayesian modeling for ecologistsUniquely suited to deal with complexity in a statistically coherent way, Bayesian modeling has become an indispensable tool for ecological research. This book teaches the basic principles of mathematics and statistics needed to apply Bayesian models to the analysis of ecological data, using language non-statisticians can understand. Deemphasizing computer coding in favor of a clear treatment of model building, it starts with a definition of probability and proceeds step-by-step through distribution theory, likelihood, simple Bayesian models, and hierarchical Bayesian models. Now revised and expanded, Bayesian Models enables students and practitioners to gain new insights from ecological models and data properly tempered by uncertainty.Covers the basic rules of probability needed to model diverse types of ecological data in the Bayesian frameworkShows how to write proper mathematical expressions for posterior distributions using directed acyclic graphs as templatesExplains how to use the powerful Markov chain Monte Carlo algorithm to find posterior distributions of model parameters, latent states, and missing dataTeaches how to check models to assure they meet the assumptions of model-based inferenceDemonstrates how to make inferences from single and multiple Bayesian modelsProvides worked problems for practicing and strengthening modeling skillsFeatures new chapters on spatial models and modeling missing data |
| Authors: | N. Thompson Hobbs, Mevin B. Hooten |
| Resource Type: | eBook. |
| Subjects: | Ecology--Statistical methods, Bayesian statistical decision theory |
| Categories: | SCIENCE / Life Sciences / Ecology, MATHEMATICS / Probability & Statistics / Bayesian Analysis |
| Database: | eBook Index |
| FullText | Text: Availability: 0 |
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| Header | DbId: edsebk DbLabel: eBook Index An: 4095769 RelevancyScore: 981 AccessLevel: 6 PubType: eBook PubTypeId: ebook PreciseRelevancyScore: 981.043701171875 |
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| Items | – Name: Title Label: Title Group: Ti Data: Bayesian Models : A Statistical Primer for Ecologists, 2nd Edition – Name: Abstract Label: Description Group: Ab Data: A fully updated and expanded edition of the essential primer on Bayesian modeling for ecologistsUniquely suited to deal with complexity in a statistically coherent way, Bayesian modeling has become an indispensable tool for ecological research. This book teaches the basic principles of mathematics and statistics needed to apply Bayesian models to the analysis of ecological data, using language non-statisticians can understand. Deemphasizing computer coding in favor of a clear treatment of model building, it starts with a definition of probability and proceeds step-by-step through distribution theory, likelihood, simple Bayesian models, and hierarchical Bayesian models. Now revised and expanded, Bayesian Models enables students and practitioners to gain new insights from ecological models and data properly tempered by uncertainty.Covers the basic rules of probability needed to model diverse types of ecological data in the Bayesian frameworkShows how to write proper mathematical expressions for posterior distributions using directed acyclic graphs as templatesExplains how to use the powerful Markov chain Monte Carlo algorithm to find posterior distributions of model parameters, latent states, and missing dataTeaches how to check models to assure they meet the assumptions of model-based inferenceDemonstrates how to make inferences from single and multiple Bayesian modelsProvides worked problems for practicing and strengthening modeling skillsFeatures new chapters on spatial models and modeling missing data – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22N%2E+Thompson+Hobbs%22">N. Thompson Hobbs</searchLink><br /><searchLink fieldCode="AR" term="%22Mevin+B%2E+Hooten%22">Mevin B. Hooten</searchLink> – Name: TypePub Label: Resource Type Group: TypPub Data: eBook. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Ecology--Statistical+methods%22">Ecology--Statistical methods</searchLink><br /><searchLink fieldCode="DE" term="%22Bayesian+statistical+decision+theory%22">Bayesian statistical decision theory</searchLink> – Name: SubjectBISAC Label: Categories Group: Su Data: <searchLink fieldCode="ZK" term="%22SCIENCE+%2F+Life+Sciences+%2F+Ecology%22">SCIENCE / Life Sciences / Ecology</searchLink><br /><searchLink fieldCode="ZK" term="%22MATHEMATICS+%2F+Probability+%26+Statistics+%2F+Bayesian+Analysis%22">MATHEMATICS / Probability & Statistics / Bayesian Analysis</searchLink> |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edsebk&AN=4095769 |
| RecordInfo | BibRecord: BibEntity: Classifications: – Code: 577.0727 Scheme: ddc Type: prePub Languages: – Code: eng Text: English Subjects: – SubjectFull: Ecology--Statistical methods Type: general – SubjectFull: Bayesian statistical decision theory Type: general Titles: – TitleFull: Bayesian Models : A Statistical Primer for Ecologists, 2nd Edition Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: N. Thompson Hobbs – PersonEntity: Name: NameFull: Mevin B. Hooten – PersonEntity: Name: NameFull: N. Thompson Hobbs – PersonEntity: Name: NameFull: Mevin B. Hooten IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 01 Type: published Y: 2025 – D: 03 M: 06 Type: profile Y: 2025 Identifiers: – Type: isbn-print Value: 9780691250120 – Type: isbn-electronic Value: 9780691271453 – Type: isbn-electronic Value: 9780691279879 Titles: – TitleFull: Bayesian Models : A Statistical Primer for Ecologists, 2nd Edition Type: main |
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